activity
20182022
most citedSpatially-Attentive Patch-Hierarchical Network for Adaptive Motion Deblurring

15 citations · 44 across the 11 of their papers we have counts for

collaborators

15 papers

cs.CV2022

Hybrid Transformer Based Feature Fusion for Self-Supervised Monocular Depth Estimation

Snehal Singh Tomar, Maitreya Suin, A. N. Rajagopalan

With an unprecedented increase in the number of agents and systems that aim to navigate the real world using visual cues and the rising impetus for 3D Vision Models, the importance…

cs.CV20221 cited

Unfolding a blurred image

Kuldeep Purohit, Anshul Shah, A. N. Rajagopalan

We present a solution for the goal of extracting a video from a single motion blurred image to sequentially reconstruct the clear views of a scene as beheld by the camera during th…

eess.IV2022

Image Superresolution using Scale-Recurrent Dense Network

Kuldeep Purohit, Srimanta Mandal, A. N. Rajagopalan

Recent advances in the design of convolutional neural network (CNN) have yielded significant improvements in the performance of image super-resolution (SR). The boost in performanc…

eess.IV2022

Deep Networks for Image and Video Super-Resolution

Kuldeep Purohit, Srimanta Mandal, A. N. Rajagopalan

Efficiency of gradient propagation in intermediate layers of convolutional neural networks is of key importance for super-resolution task. To this end, we propose a deep architectu…

cs.CV20221 cited

Robust Unpaired Single Image Super-Resolution of Faces

Saurabh Goswami, Rajagopalan A. N

We propose an adversarial attack for facial class-specific Single Image Super-Resolution (SISR) methods. Existing attacks, such as the Fast Gradient Sign Method (FGSM) or the Proje…

cs.CV2021

Spatially-Adaptive Image Restoration using Distortion-Guided Networks

Kuldeep Purohit, Maitreya Suin, A. N. Rajagopalan +1

We present a general learning-based solution for restoring images suffering from spatially-varying degradations. Prior approaches are typically degradation-specific and employ the…